Seq-BEL: Sequence-Based Ensemble Learning for Predicting Virus-Human Protein-Protein Interaction

Yingjun Ma; Tingting He; Yuting TanXingpeng Jiang

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Seq-BEL: Sequence-Based Ensemble Learning for Predicting Virus-Human Protein-Protein Interaction

机译：Seq-BEL: Sequence-Based Ensemble Learning for Predicting Virus-Human Protein-Protein Interaction

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Infectious diseases are currently the most important and widespread health problem, and identifying viral infection mechanisms is critical for controlling diseases caused by highly infectious viruses. Because of the lack of non-interactive protein pairs and serious imbalance between positive and negative sample ratios, the supervised learning algorithm is not suitable for prediction. At the same time, due to the lack of information on viral proteins and significant dissimilarity in sequence, some ensemble learning models have poor generalization ability. In this paper, we propose a Sequence-Based Ensemble Learning (Seq-BEL) method to predict the potential virus-human PPIs. Specifically, based on the amino acid sequence of proteins and the currently known virus-human PPI network, Seq-BEL calculates various features and similarities of human proteins and viral proteins, and then combines these similarities and features to score the potential of virus-human PPIs. The computational results show that Seq-BEL achieves success in predicting potential virus-human PPIs and outperforms other state-of-the-art methods. More importantly, Seq-BEL also has good predictive performance for new human proteins and new viral proteins. In addition, the model has the advantages of strong robustness and good generalization ability, and can be used as an effective tool for virus-human PPI prediction.

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《IEEE/ACM transactions on computational biology and bioinformatics》 |2022年第3期|1322-1333|共12页
作者
Yingjun Ma; Tingting He; Yuting TanXingpeng Jiang;
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作者单位

School of Computer, and the School of Mathematics and Statistics, Central China Normal University, Wuhan, Hubei, China;

School of Computer, and Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, Wuhan, Hubei, China;

School of Mathematics and Statistics, Central China Normal University, Wuhan, China;

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原文格式 PDF
正文语种英语
中图分类生物信息论;
关键词
Proteins; Viruses (medical); Feature extraction; Amino acids; Predictive models; Kernel; Computational modeling;

Seq-BEL: Sequence-Based Ensemble Learning for Predicting Virus-Human Protein-Protein Interaction

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